Modern day poultry producers have investigated almost every avenue to obtain greater efficiency and maximum yield. Most of these techniques rely on past data to signal where problems occurred and then try to determine cause. This accounting approach has serious limitations in figuring out what and how poultry either thrive or become unhealthy, or dead. Clearly post data cannot proactively manage a healthy poultry flock. Real-time predictive information is necessary to monitor and take corrective action. While sophisticated barn and poultry flock monitoring systems exist and allow real-time monitoring, there is not yet an attempt to gather and correlate multiple monitoring inputs into a predictive statistical model. To be successful, such a model needs a baseline indicator of poultry stress and the ability to correlate multiple streams of environmental data to changes in the baseline.
Modern poultry barns often incorporate centralized monitoring and control systems that allow for control and monitoring the following:
Feed consumption
Water consumption
Lighting schedule
Temperature inside and out
Humidity inside and out
Fan operation
Information from these types of systems are typically available as historical after-the-fact batch downloads, sometimes weeks later, as in accounting systems, as well as state-of-the art real-time monitoring and warning systems, some using a personal computer, smart phone or an internet interface. From this data, environmental anomalies, such as extreme temperatures can be monitored via warning indicators to allow evasive actions to mitigate or avoid fatal environmental stresses to the poultry flock. These systems are successful in monitoring single variables, such as temperature and humidity that can avert potential losses if acted upon quickly. Examples of methods and systems for managing and operating poultry barns are disclosed in U.S. Pat. Nos. 4,700,887; 7,751,942 and 7,904,284.
While these systems are useful, they are limited. Because of the geographical isolation and distribution of poultry barns, there are real barriers to collecting data from multiple locations simultaneously. Additionally, there is the limit to how much data can be collected and stored using traditional information systems technology of centralized processing. Typically, because of low margins inherent in running a poultry business, accounting and information services are most focused on and concerned with transaction efficiencies, running the business and have little time or resources devoted to creating a centralized monitoring system for their barn network. Without a method to consolidate environmental data, predictive correlation modeling is impossible.